On the Stability of Isolated and Interconnected Input-Queued Switches under Multiclass Traffic

In this correspondence, we discuss the stability of scheduling algorithms for input-queueing (IQ) and combined input/output queueing (CIOQ) packet switches. First, we show that a wide class of IQ schedulers operating on multiple traffic classes can achieve 100 % throughput. Then, we address the problem of the maximum throughput achievable in a network of interconnected IQ switches and CIOQ switches loaded by multiclass traffic, and we devise some simple scheduling policies that guarantee 100 % throughput. Both the Lyapunov function methodology and the fluid modeling approach are used to obtain our results

Scheduling algorithms for high-speed switches

The virtual output queued (VOQ) switching architecture was adopted for high speed switch implementation owing to its scalability and high throughput. An ideal VOQ algorithm should provide Quality of Service (QoS) with low complexity. However, none of the existing algorithms can meet these requirements. Several algorithms for VOQ switches are introduced in this dissertation in order to improve upon existing algorithms in terms of implementation or QoS features. Initially, the earliest due date first matching (EDDFM) algorithm, which is stable for both uniform and non-uniform traffic patterns, is proposed. EDDFM has lower probability of cell overdue than other existing maximum weight matching algorithms. Then, the shadow departure time algorithm (SDTA) and iterative SDTA (ISDTA) are introduced. The QoS features of SDTA and ISDTA are better than other existing algorithms with the same computational complexity. Simulations show that the performance of a VOQ switch using ISDTA with a speedup of 1.5 is similar to that of an output queued (OQ) switch in terms of cell delay and throughput. Later, the enhanced Birkhoff-von Neumann decomposition (EBVND) algorithm based on the Birkhoff-von Neumann decomposition (BVND) algorithm, which can provide rate and cell delay guarantees, is introduced. Theoretical analysis shows that the performance of EBVND is better than BVND in terms of throughput and cell delay. Finally, the maximum credit first (MCF), the Enhanced MCF (EMCF), and the iterative MCF (IMCF) algorithms are presented. These new algorithms have the similar performance as BNVD, yet are easier to implement in practice

On scheduling input queued cell switches

Output-queued switching, though is able to offer high throughput, guaranteed delay and fairness, lacks scalability owing to the speed up problem. Input-queued switching, on the other hand, is scalable, and is thus becoming an attractive alternative. This dissertation presents three approaches toward resolving the major problem encountered in input-queued switching that has prohibited the provision of quality of service guarantees. First, we proposed a maximum size matching based algorithm, referred to as min-max fair input queueing (MFIQ), which minimizes the additional delay caused by back pressure, and at the same time provides fair service among competing sessions. Like any maximum size matching algorithm, MFIQ performs well for uniform traffic, in which the destinations of the incoming cells are uniformly distributed over all the outputs, but is not stable for non-uniform traffic. Subse-quently, we proposed two maximum weight matching based algorithms, longest normalized queue first (LNQF) and earliest due date first matching (EDDFM), which are stable for both uniform and non-uniform traffic. LNQF provides fairer service than longest queue first (LQF) and better traffic shaping than oldest cell first (OCF), and EDDEM has lower probability of delay overdue than LQF, LNQF, and OCF. Our third approach, referred to as store-sort-and-forward (SSF), is a frame based scheduling algorithm. SSF is proved to be able to achieve strict sense 100% throughput, and provide bounded delay and delay jitter for input-queued switches if the traffic conforms to the (r, T) model

PABO: Mitigating Congestion via Packet Bounce in Data Center Networks

In today's data center, a diverse mix of throughput-sensitive long flows and delay-sensitive short flows are commonly presented in shallow-buffered switches. Long flows could potentially block the transmission of delay-sensitive short flows, leading to degraded performance. Congestion can also be caused by the synchronization of multiple TCP connections for short flows, as typically seen in the partition/aggregate traffic pattern. While multiple end-to-end transport-layer solutions have been proposed, none of them have tackled the real challenge: reliable transmission in the network. In this paper, we fill this gap by presenting PABO -- a novel link-layer design that can mitigate congestion by temporarily bouncing packets to upstream switches. PABO's design fulfills the following goals: i) providing per-flow based flow control on the link layer, ii) handling transient congestion without the intervention of end devices, and iii) gradually back propagating the congestion signal to the source when the network is not capable to handle the congestion.Experiment results show that PABO can provide prominent advantage of mitigating transient congestions and can achieve significant gain on end-to-end delay